Assessment of engineering behaviour of an intensely weathered swelling mudstone under full range of seasonal variation and the relationships among measured parameters
Bibliographic record
Abstract
An experimental study was conducted to investigate the physical and mechanical properties of an intensely weathered mudstone from Northeast China after wetting–drying (W–D), freezing–thawing (F–T), and wetting–drying–freezing–thawing (W–D–F–T) cycles. These cyclic climatic processes have significant effects on the volume, microstructure, stress–strain behaviour, shear strength, electrical resistivity, and P-wave velocity of the samples. The variation in electrical resistivity exhibits an inverse correlation with the volume change, and a strong relationship can be observed between the electrical resistivity and porosity. The cohesion decreases with increasing number of cycles, while the internal friction angle slightly increases; these relationships can be caused by the presence of cracks and large voids and by the increase in the aggregate size and density during the drying and freezing processes, respectively. Moreover, the W–D–F–T cycles have a greater influence on the shear strength than do either the W–D or F–T cycles. This phenomenon is similar to that observed in the P-wave velocity, and the relationships between the shear strength parameters and P-wave velocity are also explored. This study provides nondestructive methods of predicting the deformation and shear strength of mudstones in seasonally frozen regions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".